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<p>对于编程和计算机科学来说，数据结构是主要的主题，几乎涉及所有计算机领域。</p>
<p>本文介绍 <code>python</code> 中的一些数据结构。</p>
<a id="more"></a>
<h1 id="1-什么是数据结构"><a href="#1-什么是数据结构" class="headerlink" title="1. 什么是数据结构"></a>1. 什么是数据结构</h1><p>计算机科学中，数据结构是一种为了便于数据获取和修改的组织、管理和存储的形式。所有编程语言中，列表、字典和数组是最简单的数据结构。尽管语法不同，但是其内在的逻辑是相同的。因此，本文介绍的例子也适用于其它编程语言。</p>
<h1 id="2-字典、映射、哈希表"><a href="#2-字典、映射、哈希表" class="headerlink" title="2. 字典、映射、哈希表"></a>2. 字典、映射、哈希表</h1><p><code>Python</code> 中的字典（<code>dictionary</code>）可以用来存储任意数据，每条数据都有一个关键词。映射（<code>map</code>）也被称为哈希表（<code>hash table</code>）、查找表（<code>lookup table</code>）或者关联数组（<code>associative array</code>）。它可以更轻松地组织与特定关键字关联的数据，并以更有条理的形式呈现。</p>
<p>比如，用字典来存储每个人的年龄：</p>
<figure class="highlight python"><table><tr><td class="gutter"><pre><span class="line">1</span><br><span class="line">2</span><br><span class="line">3</span><br><span class="line">4</span><br><span class="line">5</span><br></pre></td><td class="code"><pre><span class="line">data = &#123;</span><br><span class="line">    <span class="string">'Mark'</span>: <span class="number">12</span>,</span><br><span class="line">    <span class="string">'Alice'</span>: <span class="number">23</span>,</span><br><span class="line">    <span class="string">'David'</span>: <span class="number">8</span></span><br><span class="line">&#125;</span><br></pre></td></tr></table></figure>
<p>当我们想要查看特定的人的年龄时：</p>
<figure class="highlight python"><table><tr><td class="gutter"><pre><span class="line">1</span><br><span class="line">2</span><br><span class="line">3</span><br></pre></td><td class="code"><pre><span class="line">data[<span class="string">'Mark'</span>]</span><br><span class="line"></span><br><span class="line"><span class="comment"># Output: 12</span></span><br></pre></td></tr></table></figure>
<blockquote>
<p>当然，你可以把数据写在同一行内，但是如果数据量比较大的时候，卸载一行看起来会比较乱。</p>
</blockquote>
<h2 id="2-1-OrderedDict-defaultdict-ChainMap"><a href="#2-1-OrderedDict-defaultdict-ChainMap" class="headerlink" title="2.1 OrderedDict, defaultdict, ChainMap"></a>2.1 <code>OrderedDict</code>, <code>defaultdict</code>, <code>ChainMap</code></h2><ul>
<li>字典是无序的，如果我们想按照顺序来存储数据，显然原生的字典就无能为力了，这个时候就可以用 <code>OrderedDict</code>：</li>
</ul>
<figure class="highlight python"><table><tr><td class="gutter"><pre><span class="line">1</span><br><span class="line">2</span><br><span class="line">3</span><br><span class="line">4</span><br><span class="line">5</span><br><span class="line">6</span><br><span class="line">7</span><br></pre></td><td class="code"><pre><span class="line"><span class="keyword">import</span> collections <span class="keyword">as</span> cs</span><br><span class="line"></span><br><span class="line">dict1 = cs.OrderedDict(</span><br><span class="line">    Mark=<span class="number">12</span>,</span><br><span class="line">    Alice=<span class="number">23</span>,</span><br><span class="line">    David=<span class="number">8</span></span><br><span class="line">)</span><br></pre></td></tr></table></figure>
<p>查看一下 <code>dcit1</code>：</p>
<figure class="highlight python"><table><tr><td class="gutter"><pre><span class="line">1</span><br><span class="line">2</span><br><span class="line">3</span><br></pre></td><td class="code"><pre><span class="line">print(dict1)</span><br><span class="line"></span><br><span class="line"><span class="comment"># Ouput: ([('Mark', 12), ('Alice', 22), ('David', 8)])</span></span><br></pre></td></tr></table></figure>
<ul>
<li>当我们从字典里面取值的时候，遇到字典里并没有对应的 key 的时候，程序就会报错。这时 <code>defaultdict</code> 就派上用场了。<code>defaultdict</code> 的作用是在于，当字典里的key不存在但被查找时，返回的不是 <code>keyError</code> 而是一个默认值。</li>
</ul>
<figure class="highlight python"><table><tr><td class="gutter"><pre><span class="line">1</span><br><span class="line">2</span><br><span class="line">3</span><br><span class="line">4</span><br><span class="line">5</span><br><span class="line">6</span><br></pre></td><td class="code"><pre><span class="line"><span class="keyword">from</span> collections <span class="keyword">import</span> defaultdict</span><br><span class="line"></span><br><span class="line">dict1 = defaultdict(int)</span><br><span class="line">dict2 = defaultdict(set)</span><br><span class="line">dict3 = defaultdict(str)</span><br><span class="line">dict4 = defaultdict(list)</span><br></pre></td></tr></table></figure>
<p><code>defaultdict</code> 接受 <code>int</code>, <code>set</code>, <code>str</code>, <code>list</code> 作为参数，也可以自定义函数作为参数。我们来看下，上面的例子中默认值分别是什么：</p>
<figure class="highlight python"><table><tr><td class="gutter"><pre><span class="line">1</span><br><span class="line">2</span><br><span class="line">3</span><br><span class="line">4</span><br><span class="line">5</span><br><span class="line">6</span><br><span class="line">7</span><br><span class="line">8</span><br><span class="line">9</span><br><span class="line">10</span><br></pre></td><td class="code"><pre><span class="line">print(dict1[<span class="number">1</span>]) </span><br><span class="line">print(dict2[<span class="number">1</span>])</span><br><span class="line">print(dict3[<span class="number">1</span>])</span><br><span class="line">print(dict4[<span class="number">1</span>])</span><br><span class="line"></span><br><span class="line"><span class="comment"># Output:</span></span><br><span class="line"><span class="number">0</span></span><br><span class="line">set()</span><br><span class="line"></span><br><span class="line">[]</span><br></pre></td></tr></table></figure>
<p>说明 <code>int</code> 默认值是 0，<code>set</code> 默认值是空集合，<code>str</code> 默认值是空字符串，<code>list</code> 默认值是空列表。</p>
<ul>
<li>当你有多个字典的时候，可以使用 <code>ChainMap</code> 将它们变成一个字典。</li>
</ul>
<figure class="highlight python"><table><tr><td class="gutter"><pre><span class="line">1</span><br><span class="line">2</span><br><span class="line">3</span><br><span class="line">4</span><br><span class="line">5</span><br><span class="line">6</span><br><span class="line">7</span><br><span class="line">8</span><br><span class="line">9</span><br><span class="line">10</span><br></pre></td><td class="code"><pre><span class="line"><span class="keyword">from</span> collections <span class="keyword">import</span> ChainMap</span><br><span class="line"></span><br><span class="line">dict1 = &#123;<span class="string">"1"</span>: <span class="number">1</span>, <span class="string">"2"</span>: <span class="number">2</span>&#125;</span><br><span class="line">dict2 = &#123;<span class="string">"3"</span>: <span class="number">3</span>, <span class="string">"4"</span>: <span class="number">4</span>&#125;</span><br><span class="line">main = ChainMap(dict1, dict2)</span><br><span class="line"></span><br><span class="line">print(main[<span class="string">"3"</span>] , main[<span class="string">"1"</span>])</span><br><span class="line"></span><br><span class="line"><span class="comment"># Output:</span></span><br><span class="line"><span class="number">3</span> <span class="number">1</span></span><br></pre></td></tr></table></figure>
<h1 id="3-数组型数据结构"><a href="#3-数组型数据结构" class="headerlink" title="3. 数组型数据结构"></a>3. 数组型数据结构</h1><h2 id="3-1-列表"><a href="#3-1-列表" class="headerlink" title="3.1 列表"></a>3.1 列表</h2><p>列表可以存储任意类型的数据。</p>
<figure class="highlight python"><table><tr><td class="gutter"><pre><span class="line">1</span><br><span class="line">2</span><br><span class="line">3</span><br><span class="line">4</span><br><span class="line">5</span><br><span class="line">6</span><br><span class="line">7</span><br><span class="line">8</span><br><span class="line">9</span><br><span class="line">10</span><br><span class="line">11</span><br><span class="line">12</span><br><span class="line">13</span><br><span class="line">14</span><br><span class="line">15</span><br><span class="line">16</span><br><span class="line">17</span><br></pre></td><td class="code"><pre><span class="line"><span class="comment"># from 0 to 10 value</span></span><br><span class="line">arr = [<span class="number">1</span>,<span class="number">2</span>,<span class="number">3</span>,<span class="number">4</span>,<span class="number">5</span>,<span class="number">6</span>,<span class="number">7</span>,<span class="number">8</span>,<span class="number">9</span>,<span class="number">10</span>]</span><br><span class="line"></span><br><span class="line"><span class="comment"># String Array</span></span><br><span class="line">arr1 = [<span class="string">"a"</span> , <span class="string">"b"</span> , <span class="string">"c"</span>]</span><br><span class="line"></span><br><span class="line"><span class="comment"># Get First Indexing</span></span><br><span class="line">arr1[<span class="number">0</span>]</span><br><span class="line"></span><br><span class="line"><span class="comment"># Get from 0 to 4</span></span><br><span class="line">arr[<span class="number">0</span>:<span class="number">4</span>]</span><br><span class="line"></span><br><span class="line"><span class="comment"># Deleting Element</span></span><br><span class="line"><span class="keyword">del</span> arr[<span class="number">0</span>]</span><br><span class="line"></span><br><span class="line"><span class="comment"># Adding Element</span></span><br><span class="line">arr.append(<span class="number">11</span>)</span><br></pre></td></tr></table></figure>
<figure class="highlight python"><table><tr><td class="gutter"><pre><span class="line">1</span><br><span class="line">2</span><br><span class="line">3</span><br></pre></td><td class="code"><pre><span class="line">print(a)</span><br><span class="line"></span><br><span class="line"><span class="comment"># Output:  [1, 2, 3, 4]</span></span><br></pre></td></tr></table></figure>
<h2 id="3-2-元组"><a href="#3-2-元组" class="headerlink" title="3.2 元组"></a>3.2 元组</h2><p>元组是另一个可以存储任意类型数据的数据结构。与列表不同的是，元组是不可变的。</p>
<figure class="highlight python"><table><tr><td class="gutter"><pre><span class="line">1</span><br><span class="line">2</span><br><span class="line">3</span><br><span class="line">4</span><br><span class="line">5</span><br><span class="line">6</span><br><span class="line">7</span><br><span class="line">8</span><br><span class="line">9</span><br><span class="line">10</span><br><span class="line">11</span><br><span class="line">12</span><br><span class="line">13</span><br><span class="line">14</span><br><span class="line">15</span><br></pre></td><td class="code"><pre><span class="line">tuple = (<span class="number">1</span> , <span class="number">2</span> , <span class="number">3</span>)</span><br><span class="line">tuple[<span class="number">0</span>]</span><br><span class="line"></span><br><span class="line"><span class="comment"># Output: 1</span></span><br><span class="line"></span><br><span class="line">tuple1 = (<span class="string">"x"</span> , <span class="number">1</span> , <span class="number">1.25</span>)</span><br><span class="line">tuple1[<span class="number">2</span>]</span><br><span class="line"></span><br><span class="line"><span class="comment"># Output: 1.25</span></span><br><span class="line"></span><br><span class="line"><span class="comment"># you'll get error</span></span><br><span class="line"><span class="keyword">del</span> tuple[<span class="number">0</span>]</span><br><span class="line">tuple[<span class="number">1</span>] = <span class="string">"y"</span></span><br><span class="line"></span><br><span class="line"><span class="comment"># 报错</span></span><br></pre></td></tr></table></figure>
<h2 id="3-3-array-数组"><a href="#3-3-array-数组" class="headerlink" title="3.3 array 数组"></a>3.3 <code>array</code> 数组</h2><p><code>python</code> 的 <code>array</code> 模块存储的数据包括整型、浮点型等等，它的空间占用率会更低。因为 <code>array</code> 只接受相同类型的数据。</p>
<figure class="highlight python"><table><tr><td class="gutter"><pre><span class="line">1</span><br><span class="line">2</span><br><span class="line">3</span><br><span class="line">4</span><br><span class="line">5</span><br></pre></td><td class="code"><pre><span class="line"><span class="comment"># Accessing array</span></span><br><span class="line"><span class="keyword">from</span> array <span class="keyword">import</span> array</span><br><span class="line"></span><br><span class="line"><span class="comment"># use type code</span></span><br><span class="line">arr = array(<span class="string">"f"</span> , [<span class="number">1.0</span> , <span class="number">1.2</span>])</span><br></pre></td></tr></table></figure>
<h2 id="3-4-字符串——字符编码的数组"><a href="#3-4-字符串——字符编码的数组" class="headerlink" title="3.4 字符串——字符编码的数组"></a>3.4 字符串——字符编码的数组</h2><p>字符串可以节省空间，因为它们被密集打包并专门处理特定的数据类型。 如果要保存 <code>Unicode</code> 文本，则应使用字符串。</p>
<figure class="highlight python"><table><tr><td class="gutter"><pre><span class="line">1</span><br><span class="line">2</span><br><span class="line">3</span><br><span class="line">4</span><br><span class="line">5</span><br><span class="line">6</span><br></pre></td><td class="code"><pre><span class="line">str = <span class="string">"55555"</span></span><br><span class="line">emoji = <span class="string">"😀"</span></span><br><span class="line"></span><br><span class="line">print(str , emoji)</span><br><span class="line"></span><br><span class="line"><span class="comment"># Outtput: 55555 😀</span></span><br></pre></td></tr></table></figure>
<h2 id="3-5-字节-amp-字节数组"><a href="#3-5-字节-amp-字节数组" class="headerlink" title="3.5 字节 &amp; 字节数组"></a>3.5 字节 &amp; 字节数组</h2><p>字节（<em>Bytes</em>）存储的是 0 到 255 的数字，如果超过了这个范围程序会报错。</p>
<figure class="highlight python"><table><tr><td class="gutter"><pre><span class="line">1</span><br><span class="line">2</span><br><span class="line">3</span><br></pre></td><td class="code"><pre><span class="line">x = bytes([<span class="number">1</span> , <span class="number">2</span> , <span class="number">3</span>])</span><br><span class="line">y = bytes([<span class="number">-1</span> , <span class="number">2</span> , <span class="number">3</span>])</span><br><span class="line">z = bytes([<span class="number">100</span> , <span class="number">200</span> , <span class="number">300</span>])</span><br></pre></td></tr></table></figure>
<figure class="highlight python"><table><tr><td class="gutter"><pre><span class="line">1</span><br><span class="line">2</span><br><span class="line">3</span><br></pre></td><td class="code"><pre><span class="line">Output: <span class="string">b'\x01\x02\x03'</span></span><br><span class="line">Output: error</span><br><span class="line">Output: error</span><br></pre></td></tr></table></figure>
<h1 id="4-集合-amp-多数组数据结构"><a href="#4-集合-amp-多数组数据结构" class="headerlink" title="4. 集合 &amp; 多数组数据结构"></a>4. 集合 &amp; 多数组数据结构</h1><h2 id="4-1-集合"><a href="#4-1-集合" class="headerlink" title="4.1 集合"></a>4.1 集合</h2><p>集合中不能包含相同的数据，且集合存储的是无序的数据。</p>
<figure class="highlight python"><table><tr><td class="gutter"><pre><span class="line">1</span><br><span class="line">2</span><br><span class="line">3</span><br><span class="line">4</span><br></pre></td><td class="code"><pre><span class="line">set = &#123;<span class="number">1</span> , <span class="number">2</span> , <span class="number">3</span>&#125;</span><br><span class="line"></span><br><span class="line">set.add(<span class="number">4</span>)</span><br><span class="line">set.remove(<span class="number">3</span>)</span><br></pre></td></tr></table></figure>
<h2 id="4-2-Frozen-Set"><a href="#4-2-Frozen-Set" class="headerlink" title="4.2 Frozen Set"></a>4.2 Frozen Set</h2><p>原始的集合元素可增可删，如果我们不想让集合发生改变，可以使用 <code>frozenset</code> 方法：</p>
<figure class="highlight python"><table><tr><td class="gutter"><pre><span class="line">1</span><br><span class="line">2</span><br><span class="line">3</span><br><span class="line">4</span><br></pre></td><td class="code"><pre><span class="line">frozen = frozenset(&#123;<span class="string">"x"</span> , <span class="string">"y"</span> , <span class="string">"z"</span>&#125;)</span><br><span class="line">frozen.add(<span class="string">"k"</span>)</span><br><span class="line"></span><br><span class="line"><span class="comment"># 报错</span></span><br></pre></td></tr></table></figure>
<h2 id="4-3-Counter"><a href="#4-3-Counter" class="headerlink" title="4.3 Counter"></a>4.3 Counter</h2><p><code>counter</code> 可以对多个集合进行合并，并且可以对每个元素进行计数，得到每个元素的个数。</p>
<figure class="highlight python"><table><tr><td class="gutter"><pre><span class="line">1</span><br><span class="line">2</span><br><span class="line">3</span><br><span class="line">4</span><br><span class="line">5</span><br><span class="line">6</span><br><span class="line">7</span><br><span class="line">8</span><br><span class="line">9</span><br><span class="line">10</span><br><span class="line">11</span><br></pre></td><td class="code"><pre><span class="line"><span class="keyword">from</span> collections <span class="keyword">import</span> Counter</span><br><span class="line"></span><br><span class="line">merge = Counter()</span><br><span class="line"></span><br><span class="line">fruits = &#123;<span class="string">"apple"</span> , <span class="string">"banana"</span> , <span class="string">"orange"</span>&#125;</span><br><span class="line">merge.update(fruits)</span><br><span class="line">print(merge)</span><br><span class="line"></span><br><span class="line">fruits1 = &#123;<span class="string">"apple"</span> , <span class="string">"banana"</span> , <span class="string">"watermelon"</span>&#125;</span><br><span class="line">merge.update(fruits1)</span><br><span class="line">print(merge)</span><br></pre></td></tr></table></figure>
<figure class="highlight python"><table><tr><td class="gutter"><pre><span class="line">1</span><br><span class="line">2</span><br></pre></td><td class="code"><pre><span class="line">&#123;<span class="string">'orange'</span>: <span class="number">1</span>, <span class="string">'apple'</span>: <span class="number">1</span>, <span class="string">'banana'</span>: <span class="number">1</span>&#125;)</span><br><span class="line">&#123;<span class="string">'apple'</span>: <span class="number">2</span>, <span class="string">'banana'</span>: <span class="number">2</span>, <span class="string">'orange'</span>: <span class="number">1</span>, <span class="string">'watermelon'</span>: <span class="number">1</span>&#125;)</span><br></pre></td></tr></table></figure>
<h1 id="5-堆栈"><a href="#5-堆栈" class="headerlink" title="5. 堆栈"></a>5. 堆栈</h1><p>堆栈是支持用于插入和删除的快速输入/输出语义 (LIFO) 的项目集合。与数组和列表不同，你不能做随机访问，你需要使用函数进行插入和删除。</p>
<h2 id="5-1-list-实现堆栈"><a href="#5-1-list-实现堆栈" class="headerlink" title="5.1 list 实现堆栈"></a>5.1 <code>list</code> 实现堆栈</h2><p>你可以用 <code>append</code> 把数据加到最后，再用<code>pop</code>从 LIFO 队列中取出。</p>
<figure class="highlight python"><table><tr><td class="gutter"><pre><span class="line">1</span><br><span class="line">2</span><br><span class="line">3</span><br><span class="line">4</span><br><span class="line">5</span><br><span class="line">6</span><br><span class="line">7</span><br><span class="line">8</span><br><span class="line">9</span><br><span class="line">10</span><br><span class="line">11</span><br><span class="line">12</span><br></pre></td><td class="code"><pre><span class="line">stack = []</span><br><span class="line"></span><br><span class="line">stack.append(<span class="number">1</span>)</span><br><span class="line">stack.append(<span class="number">2</span>)</span><br><span class="line">stack.append(<span class="number">3</span>)</span><br><span class="line"></span><br><span class="line">print(stack)</span><br><span class="line"></span><br><span class="line">stack.pop()</span><br><span class="line">stack.pop()</span><br><span class="line"></span><br><span class="line">print(stack)</span><br></pre></td></tr></table></figure>
<figure class="highlight python"><table><tr><td class="gutter"><pre><span class="line">1</span><br><span class="line">2</span><br></pre></td><td class="code"><pre><span class="line"><span class="comment"># Output: [1,2,3]</span></span><br><span class="line"><span class="comment"># Output: [1]</span></span><br></pre></td></tr></table></figure>
<h2 id="5-2-deque-实现堆栈"><a href="#5-2-deque-实现堆栈" class="headerlink" title="5.2 deque 实现堆栈"></a>5.2 <code>deque</code> 实现堆栈</h2><p><code>deque</code> 与列表的区别还支持在固定时间添加和删除数组开头的元素。</p>
<p>因此，它比列表更有效、更快。 它还支持随机访问。</p>
<p>如果您尝试删除双端队列之间的数据，您可能会失去性能，主要原因是直到两端的所有元素都移动以腾出空间或填补空白。</p>
<figure class="highlight python"><table><tr><td class="gutter"><pre><span class="line">1</span><br><span class="line">2</span><br><span class="line">3</span><br><span class="line">4</span><br><span class="line">5</span><br><span class="line">6</span><br><span class="line">7</span><br><span class="line">8</span><br><span class="line">9</span><br><span class="line">10</span><br><span class="line">11</span><br><span class="line">12</span><br><span class="line">13</span><br><span class="line">14</span><br></pre></td><td class="code"><pre><span class="line"><span class="keyword">from</span> collections <span class="keyword">import</span> deque</span><br><span class="line"></span><br><span class="line">stack = deque()</span><br><span class="line"></span><br><span class="line">stack.append(<span class="string">"a"</span>)</span><br><span class="line">stack.append(<span class="string">"b"</span>)</span><br><span class="line">stack.append(<span class="string">"c"</span>)</span><br><span class="line"></span><br><span class="line">print(stack)</span><br><span class="line"></span><br><span class="line">print(stack.pop())</span><br><span class="line">print(stack.pop())</span><br><span class="line"></span><br><span class="line">print(stack)</span><br></pre></td></tr></table></figure>
<figure class="highlight python"><table><tr><td class="gutter"><pre><span class="line">1</span><br><span class="line">2</span><br></pre></td><td class="code"><pre><span class="line"><span class="comment"># Output: deque(['a', 'b', 'c'])</span></span><br><span class="line"><span class="comment"># Output: deque(['a'])</span></span><br></pre></td></tr></table></figure>
<h1 id="6-Queues"><a href="#6-Queues" class="headerlink" title="6. Queues"></a>6. <code>Queues</code></h1><p>堆栈上的逻辑在这里略有不同，其中采用先进先出 (FIFO)，而在堆栈中采用先进后出。</p>
<p>我们这里可以使用栈中使用的 <code>list</code>和 <code>deque</code> 数据结构，也可以使用队列中的 <code>Queue</code> 类。</p>
<figure class="highlight python"><table><tr><td class="gutter"><pre><span class="line">1</span><br><span class="line">2</span><br><span class="line">3</span><br><span class="line">4</span><br><span class="line">5</span><br><span class="line">6</span><br><span class="line">7</span><br><span class="line">8</span><br><span class="line">9</span><br><span class="line">10</span><br><span class="line">11</span><br><span class="line">12</span><br></pre></td><td class="code"><pre><span class="line">queue = []</span><br><span class="line"></span><br><span class="line">queue.append(<span class="string">"x"</span>)</span><br><span class="line">queue.append(<span class="string">"y"</span>)</span><br><span class="line">queue.append(<span class="string">"z"</span>)</span><br><span class="line"></span><br><span class="line">print(queue)</span><br><span class="line"></span><br><span class="line">queue.pop(<span class="number">0</span>)</span><br><span class="line">queue.pop(<span class="number">0</span>)</span><br><span class="line"></span><br><span class="line">print(queue)</span><br></pre></td></tr></table></figure>
<figure class="highlight python"><table><tr><td class="gutter"><pre><span class="line">1</span><br><span class="line">2</span><br></pre></td><td class="code"><pre><span class="line"><span class="comment"># Output: ['x', 'y', 'z']</span></span><br><span class="line"><span class="comment"># Output: ['z']</span></span><br></pre></td></tr></table></figure>
<h2 id="6-1-deque"><a href="#6-1-deque" class="headerlink" title="6.1 deque"></a>6.1 <code>deque</code></h2><figure class="highlight python"><table><tr><td class="gutter"><pre><span class="line">1</span><br><span class="line">2</span><br><span class="line">3</span><br><span class="line">4</span><br><span class="line">5</span><br><span class="line">6</span><br><span class="line">7</span><br><span class="line">8</span><br><span class="line">9</span><br><span class="line">10</span><br><span class="line">11</span><br><span class="line">12</span><br><span class="line">13</span><br><span class="line">14</span><br></pre></td><td class="code"><pre><span class="line"><span class="keyword">from</span> collections <span class="keyword">import</span> deque</span><br><span class="line"></span><br><span class="line">queue = deque()</span><br><span class="line"></span><br><span class="line">queue.append(<span class="string">"x"</span>)</span><br><span class="line">queue.append(<span class="string">"y"</span>)</span><br><span class="line">queue.append(<span class="string">"z"</span>)</span><br><span class="line"></span><br><span class="line">print(queue)</span><br><span class="line"></span><br><span class="line">queue.popleft()</span><br><span class="line">queue.popleft()</span><br><span class="line"></span><br><span class="line">print(queue)</span><br></pre></td></tr></table></figure>
<figure class="highlight python"><table><tr><td class="gutter"><pre><span class="line">1</span><br><span class="line">2</span><br></pre></td><td class="code"><pre><span class="line"><span class="comment"># Output: deque(['x', 'y', 'z'])</span></span><br><span class="line"><span class="comment"># Output: deque(['z'])</span></span><br></pre></td></tr></table></figure>
<h2 id="6-2-queue"><a href="#6-2-queue" class="headerlink" title="6.2 queue"></a>6.2 <code>queue</code></h2><p>队列是一种结构，通过它我们可以确定队列可以容纳和存储多少数据。 它主要用于实现队列。</p>
<p>您可以通过将 <code>max size</code> 参数设置为 0 来创建无限队列，这符合 FIFO 规则。</p>
<figure class="highlight python"><table><tr><td class="gutter"><pre><span class="line">1</span><br><span class="line">2</span><br><span class="line">3</span><br><span class="line">4</span><br><span class="line">5</span><br><span class="line">6</span><br><span class="line">7</span><br><span class="line">8</span><br><span class="line">9</span><br><span class="line">10</span><br><span class="line">11</span><br><span class="line">12</span><br><span class="line">13</span><br><span class="line">14</span><br><span class="line">15</span><br><span class="line">16</span><br></pre></td><td class="code"><pre><span class="line"><span class="keyword">from</span> queue <span class="keyword">import</span> Queue</span><br><span class="line"></span><br><span class="line">queue = Queue(maxsize = <span class="number">0</span>)</span><br><span class="line"></span><br><span class="line"><span class="comment"># Adding element</span></span><br><span class="line">queue.put(<span class="number">10</span>)</span><br><span class="line">queue.put(<span class="number">20</span>)</span><br><span class="line">queue.put(<span class="number">30</span>)</span><br><span class="line"></span><br><span class="line">print(queue.queue)</span><br><span class="line"></span><br><span class="line"><span class="comment"># Removing element</span></span><br><span class="line">queue.get()</span><br><span class="line">queue.get()</span><br><span class="line"></span><br><span class="line">print(queue.queue)</span><br></pre></td></tr></table></figure>
<figure class="highlight python"><table><tr><td class="gutter"><pre><span class="line">1</span><br><span class="line">2</span><br></pre></td><td class="code"><pre><span class="line"><span class="comment"># Output: deque([10, 20, 30])</span></span><br><span class="line"><span class="comment"># Output: deque([30])</span></span><br></pre></td></tr></table></figure>
<h1 id="7-自定义数据类型"><a href="#7-自定义数据类型" class="headerlink" title="7. 自定义数据类型"></a>7. 自定义数据类型</h1><p>要更可控，您只需要您自己。 不要害怕创建和使用自己的类。 创建复杂的类有时会很累，但它会提高您的工作效率。</p>
<p>当您想通过方法向记录对象添加业务逻辑和活动时，创建自定义类是一个极好的解决方案。 然而，这意味着这些东西不再只是数据对象。</p>
<figure class="highlight python"><table><tr><td class="gutter"><pre><span class="line">1</span><br><span class="line">2</span><br><span class="line">3</span><br><span class="line">4</span><br><span class="line">5</span><br><span class="line">6</span><br><span class="line">7</span><br><span class="line">8</span><br><span class="line">9</span><br><span class="line">10</span><br><span class="line">11</span><br><span class="line">12</span><br></pre></td><td class="code"><pre><span class="line"><span class="class"><span class="keyword">class</span> <span class="title">Student</span>:</span></span><br><span class="line">    <span class="function"><span class="keyword">def</span> <span class="title">__init__</span><span class="params">(self, name, note)</span>:</span></span><br><span class="line">        self.name = name</span><br><span class="line">        self.note = note</span><br><span class="line"></span><br><span class="line">x = Student(<span class="string">"David"</span> , <span class="number">55</span>)</span><br><span class="line">y = Student(<span class="string">"Mark"</span> , <span class="number">35</span>)</span><br><span class="line"></span><br><span class="line"><span class="comment"># Access Data</span></span><br><span class="line">print(x.name , x.note)</span><br><span class="line"></span><br><span class="line">print(Student)</span><br></pre></td></tr></table></figure>
<figure class="highlight python"><table><tr><td class="gutter"><pre><span class="line">1</span><br><span class="line">2</span><br></pre></td><td class="code"><pre><span class="line"><span class="comment"># Output: David 55</span></span><br><span class="line"><span class="comment"># Output: &lt;main.Student object at 0x7f53925c2400&gt;</span></span><br></pre></td></tr></table></figure>
<h1 id="8-Reference"><a href="#8-Reference" class="headerlink" title="8. Reference"></a>8. Reference</h1><p><a href="https://mymasterdesigner.com/2021/07/06/data-structures-with-python-big-guide/" target="_blank" rel="noopener">Data Structures With Python – Big Guide</a></p>

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